INSECT-PEST DIAGNOSIS AND FORECASTING FOR ASEAN PADDY FIELDS

Presented by: Assoc. Prof. Dr. Samsuzana Abd Aziz

Smart Farming Technology Research CenterDepartment of Biological and Agricultural Engineering

ASEAN IVO Forum 2018

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GROUP MEMBERS

Malaysia Indonesia Japan

Stre

ngt

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Smart Farming Technology Research Center (SFTRC)

Research Centre of Excellence for Wireless and Photonics Network (WiPNET)

Integrated Pest management Experts, Universiti Putra Malaysia (UPM)

Asian Federation for Information Technology in Agriculture

Agricultural Informatics Experts, Bogor Agricultural University (IPB)

Agricultural and Environmental Engineering Experts, Faculty of Life and Environmental Sciences, University of Tsukuba

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PROBLEM STATEMENT• Farmers lose an estimated average of 37% of their rice crop

to pests and diseases every year.

• Many of these pest has developed resistance to many pesticides.

• Pest counting were conducted by the officers manually, which are usually time consuming and required experts to determine the type of pest.

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PROBLEM STATEMENT

• Pest population level may also be the resultant of weather parameters of several preceding weeks or months.

• There is a trend farmers uses social media platform but sometimes information given might not be accurate.

• Non DSS available in local languages make it hard for farmers to adopt.

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OBJECTIVES

Development of insect-pest diagnosis and forecasting (IPDF) mobile app, consist of two important menu: diagnosis system and forecasting system. The specific objectives of this study are:• To develop a diagnosis algorithm of the insect-pest

population on trap using imaging technologies and computational intelligence

• To incorporate weather data in forecasting the potential of insect-pest outbreak

• To translate IPDF system into a mobile app in local languages and assess the viability of the prototype

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Solution/Approach

Insect-Pest Diagnosis

and Forecasting (IPDF)

FORECASTING

ACTION

RECOMMENDATION

EVALUATION

INSPECTION

DIAGNOSIS

Insect-pest traps are

deployed on paddy

fields

Pictures from the traps are

gathered, processed and

securely archived using

imaging technologies and

computational intelligence.

The pest that are recognized

are automatically marked

Potential of insect-pest

outbreak for the next 10 days

are forecasted by incorporating weather data

Farmers receive informed

recommendation and apply

materials only as necessary (correctly and carefully)

Continuous evaluation are

conducted to improve

diagnosis and forecasting platform

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METHODOLOGY

Phases 1: Development of diagnosis algorithm for pest marking and counting (UPM)

• Insect-pest traps are deployed on experimental paddy fields at Sawah Sempadan, Tanjung Karang in the Integrated Agriculture Development Area (IADA), Barat Laut, Malaysia

Phases 2: Development of pest outbreak forecasting algorithm using weather data (University of Tsukuba)

• The weather data is collected from record book of local meteorological department or from the weather station installed at experimental sites

• Koshi Hikari rice production zone.

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METHODOLOGY

Phases 3: Translating IPDF platform into mobile app (UPM, IPB)

• The app enable users to take images on insect-pest traps at their paddy fields, upload the images and receive instant diagnosis and informed recommendation of required actions to manage the pest in the fields

Phases 4: Implementation of IPDF platform at Block J, Sawah Sempadan, Tanjung Karang in Malaysia and along Pantura (north coastal territory) paddy fields in Jawa Island Indonesia (UPM, IPB, University of Tsukuba)

• Training and workshop will be conducted for IPDF usage trial

• Assessment of IPDF platform viability is conducted through uses cases, trials, user interviews and questionnaires

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Leveraged Resources and Participants

Malaysia Indonesia Japan

Ro

les

Development of diagnosis algorithm using imaging technologies and computational intelligence

Development of model in forecasting the potential of insect-pest outbreak

Translation of insect-pest diagnosis and forecasting into mobile Apps

Deployment and viability study of IPDF system at local paddy field

Deployment and viability study of IPDF system at local paddy field

Consultation for IPDF system deployment for Malaysia and Indonesia

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Members Expertise• SFTRC

• Involve in smart farming researches since 2006 and awakened ICT center called Smart Farming Community Center at Sawah Sepadan Malaysia, Urban Farming, etc

• WIPNET• Since 2010 involved with contract research on WSN-related projects:

agricultural-precision, ICT infrastructure & monitoring, WSN standard development.

• ITAFOS• Since 2006: focusing on climate smart crop production

• Bioinformatics Engineering Laboratory, IPB• Center for research for engineering applications in agriculture

• Agricultural and Environmental Engineering, Tsukuba• Focuses mainly on human-enviromental interactions, primarily in the

field of agriculture, agricultural technologies, food science and enviromental management

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Facilities, Equipment andother Resources• Existing Facilities

• Research laboratories at UPM, IPB, Tsukuba• Meeting venues at UPM, IPB and Tsukuba• Prior engagement with farmers corporation at Sawah

Sepadan, Selangor; Pantura and Koshi Hikari.

• Equipment • PC/computing hardware and software from UPM, IPB,

Tsukuba• Researchers from UPM, IPB, Tsukuba including support staff

relevant to this project • Smart Farming Community Center at Sawah Sepadan

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EXPECTED OUTPUT

Technological Innovation• Enhancing ICT technological advancement for agriculture;• Enhancing IoT adoption and ecosystem development;• Strengthening the local SMEs' capabilities to build

innovative IoT solutions and services in agriculture; • Empowering farmers

Social Innovation• Conducting innovation programs for farming communities

such as training/workshop and ICT-related entrepreneurship events.

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Terima Kasih | Thank You | Arigato

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